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dc.contributor.authorWang, Qi*
dc.date.accessioned2021-02-11T17:30:53Z
dc.date.available2021-02-11T17:30:53Z
dc.date.issued2019*
dc.date.submitted2019-12-09 11:49:15*
dc.identifier42555*
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/51488
dc.description.abstractWith the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.*
dc.languageEnglish*
dc.subjectQA75.5-76.95*
dc.subjectT58.5-58.64*
dc.subject.othermetadata*
dc.subject.otherimage classification*
dc.subject.othersensitivity analysis*
dc.subject.otherROI detection*
dc.subject.otherresidual learning*
dc.subject.otherimage alignment*
dc.subject.otheradaptive convolutional kernels*
dc.subject.otherHough transform*
dc.subject.otherclass imbalance*
dc.subject.otherland surface temperature*
dc.subject.otherinundation mapping*
dc.subject.othermultiscale representation*
dc.subject.otherobject-based*
dc.subject.otherconvolutional neural networks*
dc.subject.otherscene classification*
dc.subject.othermorphological profiles*
dc.subject.otherhyperedge weight estimation*
dc.subject.otherhyperparameter sparse representation*
dc.subject.othersemantic segmentation*
dc.subject.othervehicle classification*
dc.subject.otherflood*
dc.subject.otherLandsat imagery*
dc.subject.othertarget detection*
dc.subject.othermulti-sensor*
dc.subject.otherbuilding damage detection*
dc.subject.otheroptimized kernel minimum noise fraction (OKMNF)*
dc.subject.othersea-land segmentation*
dc.subject.othernonlinear classification*
dc.subject.otherland use*
dc.subject.otherSAR imagery*
dc.subject.otheranti-noise transfer network*
dc.subject.othersub-pixel change detection*
dc.subject.otherRadon transform*
dc.subject.othersegmentation*
dc.subject.otherremote sensing image retrieval*
dc.subject.otherTensorFlow*
dc.subject.otherconvolutional neural network*
dc.subject.otherparticle swarm optimization*
dc.subject.otheroptical sensors*
dc.subject.othermachine learning*
dc.subject.othermixed pixel*
dc.subject.otheroptical remotely sensed images*
dc.subject.otherobject-based image analysis*
dc.subject.othervery high resolution images*
dc.subject.othersingle stream optimization*
dc.subject.othership detection*
dc.subject.otherice concentration*
dc.subject.otheronline learning*
dc.subject.othermanifold ranking*
dc.subject.otherdictionary learning*
dc.subject.otherurban surface water extraction*
dc.subject.othersaliency detection*
dc.subject.otherspatial attraction model (SAM)*
dc.subject.otherquality assessment*
dc.subject.otherFuzzy-GA decision making system*
dc.subject.otherland cover change*
dc.subject.othermulti-view canonical correlation analysis ensemble*
dc.subject.otherland cover*
dc.subject.othersemantic labeling*
dc.subject.othersparse representation*
dc.subject.otherdimensionality expansion*
dc.subject.otherspeckle filters*
dc.subject.otherhyperspectral imagery*
dc.subject.otherfully convolutional network*
dc.subject.otherinfrared image*
dc.subject.otherSiamese neural network*
dc.subject.otherRandom Forests (RF)*
dc.subject.otherfeature matching*
dc.subject.othercolor matching*
dc.subject.othergeostationary satellite remote sensing image*
dc.subject.otherchange feature analysis*
dc.subject.otherroad detection*
dc.subject.otherdeep learning*
dc.subject.otheraerial images*
dc.subject.otherimage segmentation*
dc.subject.otheraerial image*
dc.subject.othermulti-sensor image matching*
dc.subject.otherHJ-1A/B CCD*
dc.subject.otherendmember extraction*
dc.subject.otherhigh resolution*
dc.subject.othermulti-scale clustering*
dc.subject.otherheterogeneous domain adaptation*
dc.subject.otherhard classification*
dc.subject.otherregional land cover*
dc.subject.otherhypergraph learning*
dc.subject.otherautomatic cluster number determination*
dc.subject.otherdilated convolution*
dc.subject.otherMSER*
dc.subject.othersemi-supervised learning*
dc.subject.othergate*
dc.subject.otherSynthetic Aperture Radar (SAR)*
dc.subject.otherdownscaling*
dc.subject.otherconditional random fields*
dc.subject.otherurban heat island*
dc.subject.otherhyperspectral image*
dc.subject.otherremote sensing image correction*
dc.subject.otherskip connection*
dc.subject.otherISPRS*
dc.subject.otherspatial distribution*
dc.subject.othergeo-referencing*
dc.subject.otherSupport Vector Machine (SVM)*
dc.subject.othervery high resolution (VHR) satellite image*
dc.subject.otherclassification*
dc.subject.otherensemble learning*
dc.subject.othersynthetic aperture radar*
dc.subject.otherconservation*
dc.subject.otherconvolutional neural network (CNN)*
dc.subject.otherTHEOS*
dc.subject.othervisible light and infrared integrated camera*
dc.subject.othervehicle localization*
dc.subject.otherstructured sparsity*
dc.subject.othertexture analysis*
dc.subject.otherDSFATN*
dc.subject.otherCNN*
dc.subject.otherimage registration*
dc.subject.otherUAV*
dc.subject.otherunsupervised classification*
dc.subject.otherSVMs*
dc.subject.otherSAR image*
dc.subject.otherfuzzy neural network*
dc.subject.otherdimensionality reduction*
dc.subject.otherGeoEye-1*
dc.subject.otherfeature extraction*
dc.subject.othersub-pixel*
dc.subject.otherenergy distribution optimizing*
dc.subject.othersaliency analysis*
dc.subject.otherdeep convolutional neural networks*
dc.subject.othersparse and low-rank graph*
dc.subject.otherhyperspectral remote sensing*
dc.subject.othertensor low-rank approximation*
dc.subject.otheroptimal transport*
dc.subject.otherSELF*
dc.subject.otherspatiotemporal context learning*
dc.subject.otherModest AdaBoost*
dc.subject.othertopic modelling*
dc.subject.othermulti-seasonal*
dc.subject.otherSegment-Tree Filtering*
dc.subject.otherlocality information*
dc.subject.otherGF-4 PMS*
dc.subject.otherimage fusion*
dc.subject.otherwavelet transform*
dc.subject.otherhashing*
dc.subject.othermachine learning techniques*
dc.subject.othersatellite images*
dc.subject.otherclimate change*
dc.subject.otherroad segmentation*
dc.subject.otherremote sensing*
dc.subject.othertensor sparse decomposition*
dc.subject.otherConvolutional Neural Network (CNN)*
dc.subject.othermulti-task learning*
dc.subject.otherdeep salient feature*
dc.subject.otherspeckle*
dc.subject.othercanonical correlation weighted voting*
dc.subject.otherfully convolutional network (FCN)*
dc.subject.otherdespeckling*
dc.subject.othermultispectral imagery*
dc.subject.otherratio images*
dc.subject.otherlinear spectral unmixing*
dc.subject.otherhyperspectral image classification*
dc.subject.othermultispectral images*
dc.subject.otherhigh resolution image*
dc.subject.othermulti-objective*
dc.subject.otherconvolution neural network*
dc.subject.othertransfer learning*
dc.subject.other1-dimensional (1-D)*
dc.subject.otherthreshold stability*
dc.subject.otherLandsat*
dc.subject.otherkernel method*
dc.subject.otherphase congruency*
dc.subject.othersubpixel mapping (SPM)*
dc.subject.othertensor*
dc.subject.otherMODIS*
dc.subject.otherGSHHG database*
dc.subject.othercompressive sensing*
dc.titleLearning to Understand Remote Sensing Images*
dc.typebook
oapen.identifier.doi10.3390/books978-3-03897-685-1*
oapen.relation.isPublishedBy46cabcaa-dd94-4bfe-87b4-55023c1b36d0*
virtual.oapen_relation_isPublishedBy.publisher_nameMDPI - Multidisciplinary Digital Publishing Institute
virtual.oapen_relation_isPublishedBy.publisher_websitewww.mdpi.com/books
oapen.relation.isbn9783038976851*
oapen.relation.isbn9783038976844*
oapen.pages426*
oapen.volume1*
oapen.edition1st*


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